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“Time to model all life on Earth” – Agriculture?

A recent Nature Comment article discusses the need for developing GCM-like General Ecosystem Models (GEM) to simulate whole ecosystems. The article also introduced few prototypes already being developed, including the Madingley Mondel that the lead author’s institute, Microsoft Research, is developing in collaboration with UNEP World Conservation Monitoring Centre (UNEP-WCMC).

The article suggests “… coupled with models from other fields, such as economics and epidemiology, they could offer a means of managing human actions and the biosphere in an integrated, consistent and evidence-based way.” This, of course, should apply to the agricultural activities and their interactions with the large ecosystems and their services. Speaking of which, ins’t it also “Time to model all agriculture on Earth” (General Agroecosystems Models – GAME)?

Microsoft Research and the UN team up to build a computational model of ecosystems across the worldMicrosoft Research and UN scientists have teamed up to build the first general-purpose computer model of whole ecosystems across the entire world. The project was detailed in a recent Nature article titled “Ecosystems: Time to model all life on Earth,” which unfortunately requires a subscription.

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Reference

Purves, D., Scharlemann, J. P. W., Harfoot, M., Newbold, T., Tittensor, D. P., Hutton, J., & Emmott, S. (2013). Ecosystems: Time to model all life on Earth. Nature, 493(7432), 295–297. doi:10.1038/493295a

Geographic targeting for the Roots, Tubers and Bananas (RTB) research program.

Cross-posted from the International Center for Tropical Agriculture (CIAT) DAPA Blogs

Researchers from IITA, Bioversity, CIAT and CIP met last week at CIAT headquarters in Cali, Colombia to advance geographic targeting and priority setting for the Roots, Tubers and Bananas (RTB) research program. Our activity is a background analysis for the larger RTB priority setting process that extends into the middle of 2013. The aim of the work is to consider the geographic dimensions of priority setting for the RTB crops – potato, sweet potato, yam, cassava, bananas, plantains and others. RTB researchers included professionals from the GIS labs of the four partner centers, economists working in impact assessment and several others. The team is analyzing problems and opportunities for RTB crop development, such as poverty and socioeconomic conditions where these crops are prevalent, biotic and abiotic constraints to crop production and yield gaps.

The key activity in the analysis looks at the spatial coincidence of RTB crops with poverty, population, demography, drought, excessive heat, soil constraints, pest and disease problems and many other considerations affecting where to target R&D interventions. Where should RTB focus efforts? What are the best bets for targeting technology to its ecological and socioeconomic niche? Our team is working to answer these questions and many more. Other activities in the project include a broad-scale yield gap analysis for identifying the places where R&E might have the most impact, places where crop yields are well below their potential. Finally, the team is creating an online digital atlas on everything related to RTB crop development.

RTB Cali Workshop Official Photograph

Nov 12-14 Roots, Tubers and Bananas workshop in Cali, Colombia at CIAT HQ. Front row Left to Right: Guy Hareau, David Brown, Henry Juarez, Bernado Creamer, Tunrayo Alabi, Elizabeth Barona, Martha del Rio Duque; Second Row: Flavio Avila, Glenn Hyman, Diemuth Pemsl, Ulrich Kleinwechter, Tahirou Abdoulaye, Ernesto Giron; Third row: Holger Kirscht, Joe Guo and Reinhard Simon.

 

The New Atlas of Crop Production Constraints and Opportunities

With a wide view of the future where plant breeders have the tools to breed crops in marginal environments with greater efficiency and accuracy for the benefit of the resource-poor farmers and their families, the Generation Challenge Programme (GCP) has carried out a broad access and proactive distribution platform as a consolidated vehicle for dissemination of knowledge, tools and services around crops breeding. The Integrated Breeding Platform (IBP) is particularly intended to boost crop productivity and resilience for smallholders in marginal environments by facilitating access to cutting-edge breeding technologies and informatics tools hitherto unavailable to developing-country breeder.

One of the useful informatics tools is called “Generation Atlas”, a GIS-based web mapping tool that allows researchers, policy analysts, students and others interested in crop improvement to explore constraints and opportunities of agricultural production throughout the world.

The new IBP Generation Atlas is a comprehensive compilation of online maps and geo-processing tools that use a combination of Google and ArcGIS Server technologies, integrated with databases like Google Fusion Tables synchronized with IFPRI and CIAT relational database management systems (RDBMS) to provide access to trial sites information from AgTrials, the Global Agricultural Trial Repository initiative, historical climate data, WorldClim data, generic soil profiles, soils from various sources and many more valuable information from HarvestChoice.

The web map about shows farming systems and trial sites from AgTrials repository. You can explore the map using your mouse, clicking on the red points or just go to the Atlas for visualizing more map layers and useful information such as weather stations, climate, global crop distribution, planting date, soils, soil constraints, seasonal drought index, failed season, population, percentage of children less than 5 yrs old stunted, phenotyping field sites, among others.

For further information you can contact to Glenn Hyman at CIAT or leave us a comment.

Try IBP Generation Atlas

RTB Workshop at CIAT in Cali, Colombia

Cross-posted on CIAT’s DAPA Blog

RTB (Roots, Tubers and Bananas) Workshop was held at CIAT‘s headquarters in Cali, Colombia on 12-14 November 2012.

We have 19 people from IITA, CIAT, CIP and Bioversity. One of our objectives is to test out cloud technology for sharing geographic information. We are using resources from the CGIAR Consortium for Spatial Information’s (CSI)  agreement with Environmental Systems Research Institute (ESRI). The technology is ArcGIS Online. The four CGIAR centers are pooling together their data and putting it in ArcGIS Online. Here below is a map of irrigated areas from the International Water Management Institute (IWMI) overlaid on a maps of John Dixon’s Farming Systems map. Use your mouse to pan and zoom around the maps. Note you can pan to different parts of the world. This blog post is calling the ArcGIS Online system and data stored on the cloud.

So far, we are quite pleased with the drawing speeds. We did have some difficulty getting everyone signed on to the system, but we did manage to do with only a 25 minute delay in our agenda. Today we are discussing input data into a multi-criteria evaluation process. Tomorrow, we split up into group according to crop, and begin thinking about the geographic dimension of RTB priorities.

For further information about the CSI geospatial platform initially used to support RTB project and soon more CGIAR CRPs, please contact your GIS Team in each center or leave us a comment here to follow up and help you anytime.

CGIAR-CSI at ArcGIS.com CGIAR Research Program on Roots, Tubers, and Bananas (RTB) Decision and Policy Analysis (DAPA) – a CIAT blog

GIS training on the road

IFPRI’s magazine, INSIGHTS, features a story of Emily Schmidt - who’s been working with Ethiopia’s Central Statistical Agency (CSA) to train statisticians across the country to use GIS for analyzing and visualizing the agricultural statistics data they produce. The close collaboration enabled CSA to produce their own series of atlases over the years. Now the successful training program is being expanded to Malawi and Mozambique.

On the Road | IFPRI Insights MagazineIn a vast, rapidly developing country like Ethiopia, data-about everything from literacy rates to the number of flour mills-is essential to policymaking. For the country’s Central Statistical Agency (CSA) and its regional branches, translating mountains of raw data into useful information to support policymaking in a timely manner is a major task.

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Central Statistical Agency of Ethiopia – Atlases IFPRI’s Ethiopia Strategy Support Program – Knowledge Sharing

 

Global forecasts of urban expansion to 2030

A new PNAS paper projects location, magnitudes, and rates of urban expansion to 2030. The supplementary information indicates the familiar Global Rural-Urban Mapping Project (GRUMP) dataset, of which IFPRI and CIAT participated the development, was used as the baseline data to create population density driver and to project for the future.

For us, working on the agricultural research, probably the rural extent is more relevant. Would the simple computation of [total pop - urban pop = rural pop] be legit, hopefully?

Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon poolsAbstract Urban land-cover change threatens biodiversity and affects ecosystem productivity through loss of habitat, biomass, and carbon storage. However, despite projections that world urban populations will increase to nearly 5 billion by 2030, little is known about future locations, magnitudes, and rates of urban expansion.

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Download full paper at PNAS (Open Access) Request to download GIS data (Esri GRID format)

Reference

Seto, K. C., Güneralp, B., & Hutyra, L. R. (2012). Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.1211658109

Tracking farmers’ mobility silently – Holy grail?

Back in 2009, Silvia Renn (World Fish) blogged her review of a Nature news article describing the possibility of using mobile phone to monitor human behaviors and public health and noted the untapped potential of such data and technology to detect human behavioral patterns in agriculture. Following up on the story, Science recently published an article more deeply mined such mobile phone-based location data and attempted to quantify the impact of human mobility on malaria (Wesolowski, Eagle, Tatem, Smith, Noor, Snow, Buckee, 2012).

Quantifying the Impact of Human Mobility on MalariaHuman movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here, we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions.

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As Silvia earlier noted, I also think such mobile phone-based location data and its mining technology could start unlocking answers to so many research questions involving human, or farmers in our case, behavior. There are, of course, concerns on the subject and their privacy, but let’s put it aside for a moment.

Farmers with mobile phones that they use to look up price information about their crops

Farmers with mobile phones that they use to look up price information about their crops (IICD via Flickr)

On one possible example, not necessarily fully relying on costly surveys, we could exactly pinpoint when, how many times during the growing season, farmers visit which fields, located where, for how long (as long as they keep carrying the mobile phone, that is). We may still need some in situ surveys, but we will have much better ideas on which types of management event happens, when, where – so that we can ask a lot more informed questions and hopefully useful answers. At some point after harvest, we could also track their travel from the field to the market, the mode of transportation, travel time, etc, to understand their market accessibility and value-chain of the product. We can even guesstimate how much production they may have this season, based on their farming product transportation to the markets. We will have better ideas on the production cost side as well.

For the public health side, we’ve been hearing the location of hospital/clinic doesn’t mean much; how many doctors and nurses there are now is a lot more critical issue – but it’s very difficult to keep track. Imagine we can keep track people’s time to travel from their home/village to the health clinic, how busy the facility is, how long they stay in the facility, what’s their next destination (another clinic, bank, or going back home); good interpretation of such information could lead us to much better real-time understanding of what’s happening on their livelihood and when/whether to trigger an alarm.

Anybody wants to put more thoughts and construct a concept note together? Let me know!

Reference

Wesolowski, A., Eagle, N., Tatem, A. J., Smith, D. L., Noor, A. M., Snow, R. W., & Buckee, C. O. (2012). Quantifying the Impact of Human Mobility on Malaria. Science, 338(6104), 267–270. doi:10.1126/science.1223467

Generating downscaled weather data using MarkSimGCM

MarkSimGCM

MarkSimGCM

 

A new paper describes the methodology used by CCAFS’ MarkSimGCM to downscale the outputs of a General Circulation Model and generate daily weather for the future climate (Jones, Thornton, 2013).

ScienceDirect.com – Agricultural Systems – Generating downscaled weather data from a suite of climate models for agricultural modelling applications► Most climate model outputs need manipulation before they can be used by agricultural modellers. ► We describe a tool to generate daily data that are somewhat characteristic of future climates. ► The method uses an amalgamation of empirical downscaling, climate typing and weather generation.

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Reference

Jones, P. G., & Thornton, P. K. (2013). Generating downscaled weather data from a suite of climate models for agricultural modelling applications. Agricultural Systems, 114, 1–5. doi:10.1016/j.agsy.2012.08.002

Tortillas on the Roaster Project

GIS based analysis on impact of climate change on maize bean systems in Central America done by CSI members:

Higher temperatures and changes in rainfall patterns could transform the agricultural landscape of Central America, threatening the livelihoods of one million maize and bean farmers, according to a pioneering report released today that for the first time takes a specific look at the impact of climate change on a local level.

Download full report from the CRS website

iOS 6′s new/forthcoming “Maps” uses, what else, CGIAR-CSI SRTM as elevation data

According to the San Francisco Chronicle, here is the list of data sources for the glorious (no, sorry) Apple Maps:

TomTom
Acxiom
AND.
CoreLogic Inc.
DigitalGlobe
DMTI
Getchee
Intermap
LeadDog
Localeze
MapData Sciences Pty LTD. Inc.
MDA Information Systems
Urban Mapping
Waze
Yelp
Department of Nautral Resources Canada
CGIAR Consortium for Spatial Information
Flickr
Geonames
GlobCover
NASA
OpenStreetMap
U.S. Census Bureau
U.S. Geological Survey
National Geospatial-intelligence Agency

Aboveground Live Woody Biomass from WHRC

National Dataset of Aboveground Live Woody Biomass Density by Woods Hole Research Center

Using a combination of co-located field measurements, LiDAR observations and imagery recorded from the Moderate Resolution Imaging Spectroradiometer (MODIS), WHRC researchers produced national level maps showing the amount and spatial distribution of aboveground carbon. Spatial resolution of 500m data were derived from field/LiDAR(GLAS)/MODIS.

Validating Agricultural Land Cover with Geo-Wiki

FYI, if you have experienced frustration on the quality of agricultural land use datasets out there (I know – who hasn’t), here is a place you can contribute your input:

Agriculture-Branch of the Geo-Wiki Project
http://agriculture.geo-wiki.org

The Geo-Wiki Project is a global network of volunteers who wish to help improve the quality of global land cover maps. Since large differences occur between existing global land cover maps, current ecosystem and land-use science lacks crucial accurate data (e.g. to determine the potential of additional agricultural land available to grow crops in Africa). Volunteers are asked to review hotspot maps of global land cover disagreement and determine, based on what they actually see in Google Earth and their local knowledge, if the land cover maps are correct or incorrect. Their input is recorded in a database, along with uploaded photos, to be used in the future for the creation of a new and improved global land cover map.

2011-10-07_143828

(Thanks Kai for the tip!)

Agriculture gets a makeover | Geospatial World (August 2011)

Media_httpwwwgeospati_igspl

From the text: “Geospatial technology, with its potential to address the complete life cycle of agriculture, is fast finding acceptance in agriculture to fulfill its responsibilities in addressing food security and as a fundamental instrument for sustainable development and poverty reduction, especially in developing nations. In the process, one of the oldest economic practices of human civilization is getting a makeover.”

Introducing UN-GGIM (Global Geospatial Information Management)

FYI, there is a new initiative by United Nations called GGIM, Global Geospatial Information Management, “… to create a formal mechanism under UN auspices where key issues and potential action can be discussed, and by involving member states as the key players.”

Website recently launched at http://ggim.un.org/

The UN Programme on Global Geospatial Information Management (GGIM) aims at playing a leading role in setting the agenda for the development of global geospatial information and to promote its use to address key global challenges. It provides a forum to liaise and coordinate among Member States, and between Member States and international organizations.

There will be their first UN Forum on GGIM in Seoul, South Korea, in October 2011. Concept note and agenda can be found here (you can find many familiar names in the list of speakers!).